• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.57-64
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• 2014

In this paper, we verify the relation between elements (active and inactive) of Russell's emotional dimension ("A Circumplex Model") to propose a new representing method. Russell's emotional dimension expresses emotional words (happy, joy, sad, nervous, etc.) as a point on the two dimensions (Arousal and Valence). It is most commonly used in many filed such as Science of Emotion & Sensibility, Human-Computer Interaction (HCI), and Psychology etc. But other researchers have insisted that Russell's emotional dimension have to be modified because of its inherent problems. Such problems included the possibility of mixed feelings, the difference of emotion and sensibility, and the difference of Arousal axis and Valence axis. Therefore, we verify relationship of A Circumplex Model's elements (active and inactive) and find how to people express their Arousal feelings using survey. We finally propose new method to express emotion in Russell's emotional dimension. Using this method, we can solve Russell's problems and compensate other researches.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.75-82
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• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.91-94
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• 2009

인공감정에 관련된 기존의 연구는 대부분 감정의 인식과 물리적 표현에 중점 되어 연구되었다. 하지만 감정은 성격에 따라 달리 표출되고, 시간에 따라 변화 양상을 갖는다. 또한 새로운 감정자극을 받기 이 전의 감정상태에 따라서 표출 될 감정은 달라진다. 본 논문은 감정을 성격, 시간, 감정간의 관계에 따라 관리하여 현재 표출될 감정을 시각화 해주는 인공감정을 제안한다. 감정을 시각화하기 위해서 본 논문의 인공감정은 감정그래프와 감정장을 갖는다. 감정그래프는 특정 감정을 성격과 시간에 따라 표현하는 2차원 형태의 그래프 이다. 감정장은 감정그래프에서 표현된 서로 다른 종류의 감정들을 시간과 감정간의 관계에 따라 시각화 해주는 3차원 형태의 모델이다. 제안된 인공감정을 통해 감정을 시각화해 보기 위해, 감정의 인식과 물리적 표현을 텍스트 기반으로 간소화시킨 시뮬레이터에 적용했다.

• International Area Studies Review
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• v.15 no.2
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• pp.225-245
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• 2011

This study investigates the effects of justice dimensions on negative emotion, consumer satisfaction after service recovery, repurchase intention and word-of-mouth intention in a context of service recovery. Behavioral intentions(repurchase intention and word-of-mouth intention) are critical to the discount store sellers' survival and success. The research model is an extension of previous studies, especially considering more recent developments in the service recovery literature. A survey using 458 customers in China was conducted, confirmatory factor analysis was conducted to test the validity of the measurement model, and AMOS analysis approach was used to gain important insights into how customer retention in the discount store business can be ensured. The results suggest that all three dimensions of justice had negative effects on negative emotion, had positive effects on satisfaction after service recovery. Negative emotion had negative effects on recovery satisfaction. Recovery satisfaction had positive effects on repurchase intention and word-of-mouth intention. Finally, this study suggests the implications of these findings and offers directions for future research.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.469-480
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• 2013

In this paper, we propose new method to reduce variance and express mixed feelings in Russell's emotional dimension(A Circumplex model). A Circumplex model shows mean and variance of emotions(joy, sad, happy, enjoy et. al.) in PAD(Pleasure, Arousal, Dominace, et. al.) dimension using self-diagnostic method(SAM: Self-Assessment-Manikin). But other researchers consistently insisted that Russell's model had two problems. First, data(emotional words) gathered by Russell's method have too big variance. So, it is difficult to separate valid value. Second, Russell's model can not properly represent mixed feelings because it has structural problem(It has a single Pleasure dimension). In order to solve these problems, we change survey methods, so that we reduce value of variance. And then we conduct survey(which can induce mixed feelings) to prove Positive/Negative(Pleasure) part in emotion and confirm that Russell's model can be used to express mixed feelings. Using this method, we can obtain high reliability and accuracy of data and Russell's model can be applied in many other fields such as bio-signal, mixed feelings, realistic broadcasting, et. al.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.31-32
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• 2013

본 논문에서는 영화의 등장인물의 성향을 파악하기 위해 시나리오의 대사로부터 감정어를 추출하고, 등장인물의 감정어들을 긍정, 부정, 중립의 3개로 단순화하여 등장인물의 성향을 가시화 시켜주는 방법을 제안한다. 대사로부터 감정어를 추출하기 위해 WordNet 기반의 감정어 추출 방법을 제안한다. WordNet은 단어 간에 상위어와 하위어, 유사어 등의 관계로 연결된 네트워크 구조의 사전이다. 이 네트워크 구조에서 최상위의 감정 항목과의 거리를 계산하여 단어별 감정량을 계산하여 대사를 30 차원의 감정 벡터로 표현한다. 등장인물별로 추출된 감정 벡터를 긍정, 부정, 중립의 3개의 차원으로 단순화 하여 등장인물의 성향을 표현한다.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.344-356
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• 2009

The purpose of this paper is to identify the causal role both emotionally based satisfaction and service reputation by examining the relationships among each dimensions of service quality, cognitive satisfaction, emotionally based satisfaction, service reputation and service loyalty in mobile telecommunication company. The results of the study are as follows: First, conviction quality had not influence on both cognitive satisfaction and emotionally based satisfaction, but tangibles quality had more influence on cognitive satisfaction than emotionally based satisfaction and responsiveness quality had more influence on emotionally based satisfaction than cognitive satisfaction. It found that there was a significant positive relationship between dimensions of the service quality, cognitive satisfaction and emotionally based satisfaction, and dimensions of the service quality affect satisfaction either directly or indirectly through emotion. Second, consumer satisfaction had more effect on service loyalty through service reputation than direct effect. Therefore, service loyalty can be build by increasing emotionally based satisfaction and service reputation to customer who is perceived as good service.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.163-164
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• 2013

최근 들어 감성공학에 관한 관심도가 증가하고 있다. 감성공학과 관련된 연구는 사람의 감정 상태를 표현하는 방법에 관한 연구가 활발히 진행되고 있다. 감정 상태를 표현하는 방법으론 1980년대 Russel이 제안한 Circumplex 모델[1]이 가장 대표적으로 사용되고 있으며, 최근에도 여러 논문[3-6]에서 이 모델을 이용하여 감정 상태를 나타낸다. 하지만 이 모델의 경우에는 사람의 감정상태를 감정차원 평면위에 하나의 점(평균, 분산)으로 표현하기 때문에, 실제 생체신호와의 연관성, 언어 및 문화 차이에 의한 다양성에 관한 연구를 진행하기에 어려움이 있다. 따라서 본 논문에서는 척도 대비 분산의 크기 값을 판단하여 하나의 점이 아닌 다수개의 점으로 나타내는 방법을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.131-138
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• 2013

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym, and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.05a
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• pp.41-42
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• 2011